- DSA - Home
- DSA - Overview
- DSA - Environment Setup
- DSA - Algorithms Basics
- DSA - Asymptotic Analysis
- Data Structures
- DSA - Data Structure Basics
- DSA - Data Structures and Types
- DSA - Array Data Structure
- DSA - Skip List Data Structure
- Linked Lists
- DSA - Linked List Data Structure
- DSA - Doubly Linked List Data Structure
- DSA - Circular Linked List Data Structure
- Stack & Queue
- DSA - Stack Data Structure
- DSA - Expression Parsing
- DSA - Queue Data Structure
- DSA - Circular Queue Data Structure
- DSA - Priority Queue Data Structure
- DSA - Deque Data Structure
- Searching Algorithms
- DSA - Searching Algorithms
- DSA - Linear Search Algorithm
- DSA - Binary Search Algorithm
- DSA - Interpolation Search
- DSA - Jump Search Algorithm
- DSA - Exponential Search
- DSA - Fibonacci Search
- DSA - Sublist Search
- DSA - Hash Table
- Sorting Algorithms
- DSA - Sorting Algorithms
- DSA - Bubble Sort Algorithm
- DSA - Insertion Sort Algorithm
- DSA - Selection Sort Algorithm
- DSA - Merge Sort Algorithm
- DSA - Shell Sort Algorithm
- DSA - Heap Sort Algorithm
- DSA - Bucket Sort Algorithm
- DSA - Counting Sort Algorithm
- DSA - Radix Sort Algorithm
- DSA - Quick Sort Algorithm
- Matrices Data Structure
- DSA - Matrices Data Structure
- DSA - Lup Decomposition In Matrices
- DSA - Lu Decomposition In Matrices
- Graph Data Structure
- DSA - Graph Data Structure
- DSA - Depth First Traversal
- DSA - Breadth First Traversal
- DSA - Spanning Tree
- DSA - Topological Sorting
- DSA - Strongly Connected Components
- DSA - Biconnected Components
- DSA - Augmenting Path
- DSA - Network Flow Problems
- DSA - Flow Networks In Data Structures
- DSA - Edmonds Blossom Algorithm
- DSA - Maxflow Mincut Theorem
- Tree Data Structure
- DSA - Tree Data Structure
- DSA - Tree Traversal
- DSA - Binary Search Tree
- DSA - AVL Tree
- DSA - Red Black Trees
- DSA - B Trees
- DSA - B+ Trees
- DSA - Splay Trees
- DSA - Range Queries
- DSA - Segment Trees
- DSA - Fenwick Tree
- DSA - Fusion Tree
- DSA - Hashed Array Tree
- DSA - K-Ary Tree
- DSA - Kd Trees
- DSA - Priority Search Tree Data Structure
- Recursion
- DSA - Recursion Algorithms
- DSA - Tower of Hanoi Using Recursion
- DSA - Fibonacci Series Using Recursion
- Divide and Conquer
- DSA - Divide and Conquer
- DSA - Max-Min Problem
- DSA - Strassen's Matrix Multiplication
- DSA - Karatsuba Algorithm
- Greedy Algorithms
- DSA - Greedy Algorithms
- DSA - Travelling Salesman Problem (Greedy Approach)
- DSA - Prim's Minimal Spanning Tree
- DSA - Kruskal's Minimal Spanning Tree
- DSA - Dijkstra's Shortest Path Algorithm
- DSA - Map Colouring Algorithm
- DSA - Fractional Knapsack Problem
- DSA - Job Sequencing with Deadline
- DSA - Optimal Merge Pattern Algorithm
- Dynamic Programming
- DSA - Dynamic Programming
- DSA - Matrix Chain Multiplication
- DSA - Floyd Warshall Algorithm
- DSA - 0-1 Knapsack Problem
- DSA - Longest Common Sub-sequence Algorithm
- DSA - Travelling Salesman Problem (Dynamic Approach)
- Hashing
- DSA - Hashing Data Structure
- DSA - Collision In Hashing
- Disjoint Set
- DSA - Disjoint Set
- DSA - Path Compression And Union By Rank
- Heap
- DSA - Heap Data Structure
- DSA - Binary Heap
- DSA - Binomial Heap
- DSA - Fibonacci Heap
- Tries Data Structure
- DSA - Tries
- DSA - Standard Tries
- DSA - Compressed Tries
- DSA - Suffix Tries
- Treaps
- DSA - Treaps Data Structure
- Bit Mask
- DSA - Bit Mask In Data Structures
- Bloom Filter
- DSA - Bloom Filter Data Structure
- Approximation Algorithms
- DSA - Approximation Algorithms
- DSA - Vertex Cover Algorithm
- DSA - Set Cover Problem
- DSA - Travelling Salesman Problem (Approximation Approach)
- Randomized Algorithms
- DSA - Randomized Algorithms
- DSA - Randomized Quick Sort Algorithm
- DSA - Karger’s Minimum Cut Algorithm
- DSA - Fisher-Yates Shuffle Algorithm
- Miscellaneous
- DSA - Infix to Postfix
- DSA - Bellmon Ford Shortest Path
- DSA - Maximum Bipartite Matching
- DSA Useful Resources
- DSA - Questions and Answers
- DSA - Selection Sort Interview Questions
- DSA - Merge Sort Interview Questions
- DSA - Insertion Sort Interview Questions
- DSA - Heap Sort Interview Questions
- DSA - Bubble Sort Interview Questions
- DSA - Bucket Sort Interview Questions
- DSA - Radix Sort Interview Questions
- DSA - Cycle Sort Interview Questions
- DSA - Quick Guide
- DSA - Useful Resources
- DSA - Discussion
Data Structures Algorithms Online Quiz
Following quiz provides Multiple Choice Questions (MCQs) related to Data Structures Algorithms. You will have to read all the given answers and click over the correct answer. If you are not sure about the answer then you can check the answer using Show Answer button. You can use Next Quiz button to check new set of questions in the quiz.
Q 1 - Which one of the below is not divide and conquer approach?
Answer : B
Explanation
Among the options, only Merge sort divides the list in sub-list, sorts and then merges them together
Answer : C
Explanation
Stack uses push() to insert an item in stack, and pop() to remove the top item from stack.
Answer : D
Explanation
Minimum number of queues required for priority queue implementation is two. One for storing actual data and one for storing priorities.
Q 4 - What is not true about insertion sort?
A - Exhibits the worst case performance when the initial array is sorted in reverse order.
B - Worst case and average case performance is Ο(n2)
C - Can be compared to the way a card player arranges his card from a card deck.
Answer : D
Explanation
All given options are true about insertion sort.
Q 5 - Time complexity of Depth First Traversal of is
Answer : A
Explanation
Using Depth First Search, we traverse the whole graph i.e. visiting all Vertices and Edges.
Q 6 - In context with time-complexity, find the odd out −
A - Deletion from Linked List.
Answer : D
Explanation
Binary heap heapify operation has time-complexity of Ο(n), while other operations have time-complexity of Ο(1) only.
Q 7 - Which of the following uses memoization?
B - Divide and conquer approach
Answer : C
Explanation
Remembering the results of previously calculated solutions is called memoization.
Q 8 - In C programming, when we remove an item from bottom of the stack, then −
Answer : B
Explanation
Stack can only be accessed from top of it.
Q 9 - Binary search tree is an example of complete binary tree with special attributes.
A - BST does not care about complete binary tree properties.
B - BST takes care of complete binary tree properties.
Answer : A
Explanation
BST does not care about complete binary tree properties.
Q 10 - Aposterior analysis are more accurate than apriori analysis because −
A - it contains the real data.
B - it assumes all other factors to be dynamic.
Answer : B
Explanation
In this analysis, actual statistics like running time and space required, are collected.